[2K4-GS-10] AI application

[2K4-GS-10-04] Structural Analysis of Audio Information in Musical Performance Instruction

Nami Iino^1,2, 〇Hiroya Miura², Hideaki Takeda¹, Masatoshi Hamanaka², Takuichi Nishimura³ (1. National Institute of Informatics, 2. RIKEN Center for Advanced Intelligence Project, 3. Japan Advanced Institute of Science and Technology)

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Keywords:Structural Analysis, GTTM, Musical Performance Instruction

Instrumental performance is one of the most difficult skills to evaluate quantitatively. There are also various ways to analyze the verbal and non-verbal information generated in the field of instruction. In our previous study, we analyzed the performance and speech segments in one-to-one classical guitar lesson, and defined instructional labels that represent the ``instructor's perspective.'' In this study, we attempted to analyze the lesson structurally by aggregating the above segment information and the information of the instructional labels assigned to them. The results indicate that there is commonality in group interpretations in the tree structure and that new labels that semantically categorize the content of teachers' speeches are useful in determining the hierarchy.